The origin and nature of brain waves as measured from the human scalp has been a topic of ongoing research. For example, the electroencephalogram (EEG) as measured from the intact human scalp is of interest in psychology and psychophysics because it can provide an indication of the activity of brain cells in the awake, alert state. Of particular use are the minute potentials evoked by sensory stimuli, for these time-locked transient wavelets show how populations of cells behave in response to afferent volleys carried by primary sensory fibers.
Whenever a brief stimulus is presented to a trainee, there is a transient brain response due to that stimulation. The signal produced in the EEG is generally very small, but it can be detected. In cases where it is possible to discern the EEG changes, either in the raw EEG or in a processed form, then there is said to be an “event-related potential” (ERP), or a “sensory evoked potential” (SEP). The evoked potential (EP) provides an indication of the effect of the stimulus on the brain, and it has been established that the EP is sensitive to changes in sensory and perceptual processes.
When muscle and eye movements are minimized by relaxation, the predominant sources of scalp potential are populations of cells in the brain, with large cortical cells providing the majority of the voltage. Due to the distribution of ions across active membranes, each cell tends to take on dipole characteristics and produce potentials which are carried to the scalp by volume conduction. When cells polarize in asynchrony, the net surface potential is small due to the cancellation of out-of-phase components. The presence of a measurable surface potential thus depends on the fact that some cells are polarizing in synchrony, generally in response to an afferent volley in which fibers are firing in unison.
Stimulation may be repetitive, or it may be non-repetitive. By repetitive, we mean that successive stimuli occur within a relatively short interval of time (e.g., less than one second), they occur at regular intervals, and that they are sustained throughout the stimulation period, which can be anywhere from under a second, to many minutes, or longer. When the stimulation is not repetitive, then it is said that there is a single EEG brain evoked potential response that is embedded in the ongoing EEG activity.
When a single brief stimulus is presented to the nervous system, the response generally consists of a single time-limited pattern, or burst, of action potentials carried along the appropriate afferent pathway. In the case of a light flash, the optic nerve carries the impulses; in the case of a click, the auditory nerve is involved. In both cases, sensory fibers first synapse at lower brain centers; second, third, and higher-order fibers then carry a volley of processed information to the appropriate sensory cortex. The cortical response in both modalities consists of a time-limited sequence of processing steps involving various areas of the brain; there is a substantial amount of information exchange or “crosstalk” between cortical centers, with pathways including lower brain areas. A sufficient number of cells are involved in these processes to give rise to measurable transient surface waves, the evoked potentials. Some evoked potential waves appear to involve predominantly localized cortical areas, others result from activity over widespread locations.
If the stimuli are provided in a successive manner so that a computer can analyze more than one of them, it is possible to extract an estimate of the averaged evoked potential, which represents a canonical, or standard, response of the brain, to the stimuli. When the stimulation is repetitive in nature, each stimulus follows the previous one by a short period of time (less than 500 milliseconds), and the successive evoked responses in the brain are found to overlap in time, so that the trailing end of one response is superimposed upon the beginning of the next.
When repetitive stimulation is applied, there is a small periodic signal introduced in the EEG. In general, a repetitive flash produces an EEG response at the same frequency as the stimulation, and harmonics may be present. When sinusoidal light is applied, there is a stabilizing effect, and an interaction with intrinsic rhythms. This is not seen in the case of flickering or square-wave light, which produces a simple train of stimulus-induced visual evoked potential waves.
Generally, steady-state evoked potentials are understood in terms of nonlinear mechanisms which involve both “driving” phenomena and the production of harmonics from a pure sinusoidal input. According to this interpretation, the evoked response is said to be nonlinear because of the presence of higher-order harmonics, plus the appearance of “resonance” phenomena observed near the alpha frequency.
However, an alternative interpretation is possible when study is limited to the responses to discrete stimuli such as brief clicks or flashes. In this case, a predominant mechanism leading to the evoked response is the linear superposition of successive discrete responses, to produce a complex periodic wave. This will be valid as long as successive stimuli arrive at intervals large enough for the recovery function to be near 100%, typically 100 msec or more.
For example, the waveforms of averaged visual evoked response elicited by spot flashes from 0.5 per second to 15 per second was visually inspected to confirm that the size and latency of evoked potential components is preserved across frequencies, and that the successive responses overlap, producing the observed response. Furthermore, the synchronous component response shown is identical in shape to the frequency spectrum of single evoked responses. This similarity in spectral energy distribution is what would be expected from a linear overlap model. In particular, a low-frequency band from 4 to 10 Hz is evident, and a higher-frequency band from 12 to 20 Hz is also evident. From these results, it is clear that repetitive visual stimulation produces a periodic evoked potential in the EEG, and that the frequency characteristics of this periodic wave can be predicted by using simple linear superposition.
Further rationale for using this approach in neurofeedback includes the observation that transient evoked potentials exhibit correlations with attention and mental task. For example, evoked potentials show systematic differences in clinical populations, particularly with regard to ADD and ADHD. These findings are consistent with the understanding that the speed of cortical response is one factor that determines the frequency distribution of an EEG rhythm.
The relationship between late ERP components and endogenous rhythms becomes clear if one considers the commonalities, as well as the differences, between evoked and intrinsically generated conical activity. In the case of endogenous rhythms, interaction between the cortical centers and the thalamic nuclei produce interactive sequences of afferent and efferent bursts, which are accompanied by sequences of cortical responses. In essence, an endogenous rhythm consists of a train of “intrinsic evoked potentials,” which are elicited by thalamocortical interaction, rather than by sensory stimulation. A sensory evoked potential, on the other hand, consists of the canonical response to a particular sensory input that is specified in time. In both cases, the frequency characteristics of the individual cortical responses become manifested in the power spectral density of the resulting EEG wave. Since later components of individual cortical responses produce lower frequencies in the composite power spectrum, it is reasonable to expect a cortex that produces increased or delayed late components in a sensory evoked potential to also show increased energy in low frequencies in endogenous EEG activity.
However, sensory evoked potentials are—difficult to measure because they represent the activity of only a small portion of the cells producing surface potentials, and are thus buried in background EEG noise. The duration of a typical visual or auditory evoked potential does not exceed one second, and only the early part, which comprises the first 250 milliseconds, is consistently repeatable. The later parts may vary considerably within subjects from moment to moment, and have been found to depend strongly on stimulus meaning, uncertainty, and other interpretive factors. Some form of signal-to-noise improvement is therefore necessary, and this implies a time delay for the gathering and processing of a large number of noisy responses in order to provide an evoked potential estimate in which the noise level has been reduced.
Evoked potentials are generally measured by averaging, and this requires one to two minutes for the acquisition of a single wave estimate. Since ongoing brain processes may produce evoked potential changes in mere seconds, averaging does not provide a suitable means of studying dynamic changes in brain activity. This is because the raw responses must be measured over a period of many seconds or minutes; during this time, changes due to attention, alertness, or other short-term modulations cannot in themselves be measured. On the contrary, such changes introduce signal variance which further degrades the accuracy of the final evoked potential estimate.
Several techniques are available for measuring evoked responses in a more rapid manner. One which is well suited to real-time brain monitoring is synchronous filtering of steady-state evoked potentials. By combining repetitive stimulation with synchronous filtering, it becomes possible to monitor the changing of the evoked wavelets over shortened time periods, as limited by the filtering response time-constant. This technique has the capability for rapid and ongoing measurement of evoked activity, and can respond accurately to show changes occurring over periods as short as five seconds. However, this technique has only been explored from a purely psychophysical standpoint; its application to cognitive monitoring is as of yet unexplored.